• Journal of the Korean Society of Radiology
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• v.8 no.7
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• pp.377-382
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• 2014

Because of using computer system in the field of medical radiology, many artifacts which can not be seen in film/screen system are being created, especially ghosting artifacts. This artifacts could be yielded by taking advantage of a flat panel Thin-Film Transistor array detector. Ghosting artifacts can be rarely seen in clinical practice when an image that has a high-contrast object within a region of high exposure is quickly followed by another image that puts the high-contrast ghosting image in an area of lower radiation exposure. In this experiment, the ghosting artifacts were minimized for approximately 3 minutes with the unaided eye and almost disappeared for 6 minutes quantitatively between exposures. Moreover, the artifacts were influenced by more tube voltage than current and those depended not upon the number of readout cycles, but upon time.

• Journal of the Optical Society of Korea
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• v.17 no.3
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• pp.255-261
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• 2013

Scene-based nonuniformity correction techniques for infrared focal-plane arrays have been widely considered as a key technology, and various algorithms have been proposed to compensate for fixed-pattern noise. However, the existed algorithms' capability is always restricted by the problems of convergence speed and ghosting artifacts. In this paper, an effective scene-based nonuniformity correction method is proposed to solve these problems. The algorithm is an improvement over the constant statistics method and a temporal median is utilized with the Gaussian kernel to estimate the nonuniformity parameters. Also theoretical analysis is conducted to demonstrate that effective ghosting artifacts elimination and superior convergence speed can be obtained with the proposed method. Finally, the performance of the proposed technique is tested with infrared image sequences with simulated nonuniformity and with infrared imagery with real nonuniformity. The results show the proposed method is able to estimate each detector's gain and to offset reliably and that it performs better in increasing convergence speed and reducing ghosting artifacts compared with the conventional techniques.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.15-18
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• 1990

In abdominal NMR imaging the respiratory ordering techniques have been successfully used to remove the ghosting artifacts arising from the respiratory motion. In the existing respiratory ordering schemes, however, it is generally accepted that blurring of the moving parts still remains as in the signal averaging technique. A new optimal respiratory ordering scheme which can correct the blurring as well as the ghosting artifacts is theoretically derived through the analysis of the phase encoding directional motion effects in Fourier imaging. The performance of the optimal respiratory ordering scheme is experimentally confirmed together with a suboptimal ordering scheme which is suggested as a compromise for the practicality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5419-5435
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• 2017

The construction of panoramic images on smartphones and low-powered devices is a challenging task. In this paper, we propose a new approach for smoothly stitching images on mobile phones in the presence of moving objects in the scene. Our main contributions include handling moving object problems, reducing processing time, and generating rectangular panoramic images. First, unique and robust feature points are extracted using fast ORB method and a feature matching technique is applied to match the extracted feature points. After obtaining good matched feature points, we employ the non-deterministic RANSAC algorithm to discard wrong matches, and the hommography transformation matrix parameters are estimated with the algorithm. Afterward, we determine precise overlap regions of neighboring images and calculate their absolute differences. Then, thresholding operation and noise removal filtering are applied to create a mask of possible moving object regions. Sequentially, an optimal seam is estimated using dynamic programming algorithm, and a combination of linear blending with the mask information is applied to avoid seam transition and ghosting artifacts. Finally, image-cropping operation is utilized to obtain a rectangular boundary image from the stitched image. Experiments demonstrate that our method is able to produce panoramic images quickly despite the existence of moving objects.

• Journal of the Korean Society of Radiology
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• v.10 no.8
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• pp.629-635
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• 2016

ACR phantom for quality control of magnetic resonance imaging equipment can evaluate magnetic resonance imaging picture quality through various structures within the phantom. In this study, percent Signal Ghosting and Slice position accuracy of imaging could be analyzed by attaching implant and the wire for correction of tooth using ACR phantom in Head coil of 3.0T equipment. In the T1 weighted imaging of the first slice and the eleventh slice of implant, the slice position accuracy appeared to be good in ingress bandwidth 300, and it was good in ingress bandwidth 130 when wire for correction was attached. Percent Signal Ghosting in the seventh slice of SE T1 weighted imaging, implant and wire for correction added all appeared to be good when ingress bandwidth was 230. It is thought that in case of implant dental prosthesis patients in brain exam using magnetic resonance imaging, optimum image can be obtained by changing ingress bandwidth.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.205-208
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• 2022

Multi-exposure high dynamic range (HDR) image reconstruction, the task of reconstructing an HDR image from multiple low dynamic range (LDR) images in a dynamic scene, often produces ghosting artifacts caused by camera motion and moving objects and also cannot deal with washed-out regions due to over or under-exposures. While there has been many deep-learning-based methods with motion estimation to alleviate these problems, they still have limitations for severely moving scenes. They also require large parameter counts, especially in the case of state-of-the-art methods that employ attention modules. To address these issues, we propose a frequency domain approach based on the idea that the transform domain coefficients inherently involve the global information from whole image pixels to cope with large motions. Specifically we adopt Residual Fast Fourier Transform (RFFT) blocks, which allows for global interactions of pixels. Moreover, we also employ Depthwise Overparametrized convolution (DO-conv) blocks, a convolution in which each input channel is convolved with its own 2D kernel, for faster convergence and performance gains. We call this LFFNet (Lightweight Frequency Fusion Network), and experiments on the benchmarks show reduced ghosting artifacts and improved performance up to 0.6dB tonemapped PSNR compared to recent state-of-the-art methods. Our architecture also requires fewer parameters and converges faster in training.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.446-449
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• 2009

In this paper, we present a novel method for reconstructing a super-resolution image using multi-view low-resolution images captured for depth varying scene without requiring complex analysis such as depth estimation and feature matching. The proposed method is based on the iterative back projection technique that is extended to the 3D volume domain (i.e., space + depth), unlike the conventional superresolution methods that handle only 2D translation among captured images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.74-79
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• 2011

HDR(high dynamic range) imaging techniques supports wider dynamic range than normal images captured from general still camera. These usually need several shots to obtain LDR(low dynamic range) images, causing ghosting artifacts. Accordingly, this paper suggests a method to generate new LDR images from a single Bayer image using Exposure LUT(look-up table) by considering channel dependency. We prior construct exposure LUT for each RGB channel, showing the relationship between input and average output luminance values. In the process, by applying the average luminance of input image and current exposure to LUT, new exposures which are determined by user choice are first estimated. Next, LDR images which are corresponded to new exposures are generated based on each LUT. Saturated areas are improved by considering channel dependency in the last procedure. In the experimental comparison, high PSNR values are obtained between estimated and captured images. Also, we have similar appearance on displayed images.